With the introduction of compact disks, digital video disks, portable digital media players, digital cameras, digital wireless networks, and digital media delivery over the Internet, digital media (still images, video and audio) has become commonplace. Engineers use a variety of techniques to process digital media efficiently while still maintaining quality of the digital media.
In video and imaging systems, color generally is represented as vector coordinates in a multi-dimensional “color space” having three or more color channels. Common examples include the well-known classes of RGB and YUV color spaces. The RGB color spaces specify pixel values using coordinates that represent intensities of red, green and blue light, respectively. The YUV color spaces specify pixel values using coordinates that represent a luminance or chrominance value.
Currently, many image capture, processing and display devices can only handle pixel values with a small dynamic range of 256 (28) discrete values per color channel, represented by 8 bits. Some devices can handle up to a 10- or 12-bit dynamic range per color channel. However, the human vision system can detect a wide luminance range of 14 orders of magnitude, which translates to around 46 bits. Luminance values in nature can be as high as 108 candela/m2 in bright sunlight, and as low as 10−6 candela/m2 on the underside of a rock on a moonless night.
High dynamic range (HDR) imaging presents a more versatile and natural image representation in line with the human vision system. HDR images can present a dynamic range higher than the traditional 8-bit, 10-bit and 12-bit representations to achieve a far higher image quality. HDR images can be used in the same kinds of devices and software tools that process conventional images if the HDR image format is compatible with the device or tool. Several HDR image formats have been developed, and cameras, computer graphics and display devices have begun to produce process and display images with increasing dynamic ranges. The pixel value in an HDR image is commonly represented as floating point data or integer data.
When the number of bits used to represent a pixel in an HDR image exceeds the number of bits that a lower dynamic range codec can handle, adjustments must be made. For example, and encoder can simply truncate the pixel information to reduce the number of bits. However, simple truncation can lead to visible artifacts in the decoded picture.
Whatever the benefits of previous techniques, they do not have the advantages of the techniques and tools presented below.